<![CDATA[Fuzzy logic has emerged as an essential computational paradigm for addressing uncertainty and nonlinearity in engineering systems. This paper presents a comprehensive study and application of fuzzy membership functions implemented in MATLAB for system optimization and control. Various types of membership functions—triangular, trapezoidal, Gaussian, generalized bell, and sigmoidal—are analyzed based on their shape characteristics, adaptability, and computational behavior. The study further demonstrates how these functions can be effectively utilized in the design of fuzzy controllers and optimization models to enhance decision precision in nonlinear environments. MATLAB scripts are developed to generate and evaluate membership functions dynamically, providing visual and numerical comparisons of their response profiles. The results highlight that Gaussian and bell-shaped functions offer smoother transitions and higher flexibility in representing gradual changes, making them ideal for control applications. The study contributes to improving the understanding of fuzzy modelling techniques, particularly in optimizing control responses and decision systems within uncertain environments.]]>
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